ABSTRACT Little is known about the molecular basis of differences in behavior among individuals. Here we report consistent novelty-seeking behavior, across different contexts, among honey bees in their tendency to scout for food sources and nest sites, and we reveal some of the molecular underpinnings of this behavior relative to foragers that do not scout. Food scouts showed extensive differences in brain gene expression relative to other foragers, including differences related to catecholamine, glutamate, and γ-aminobutyric acid signaling. Octopamine and glutamate treatments increased the likelihood of scouting, whereas dopamine antagonist treatment decreased it. These findings demonstrate intriguing similarities in human and insect novelty seeking and suggest that this trait, which presumably evolved independently in these two lineages, may be subserved by conserved molecular components.

[Show abstract][Hide abstract]ABSTRACT: Insects are the most diverse group of organisms on the planet. Variation in gene expression lies at the heart of this biodiversity and recent advances in sequencing technology have spawned a revolution in researchers' ability to survey tissue-specific transcriptional complexity across a wide range of insect taxa. Increasingly, studies are using a comparative approach (across species, sexes and life stages) that examines the transcriptional basis of phenotypic diversity within an evolutionary context. In the present review, we summarize much of this research, focusing in particular on three critical aspects of insect biology: morphological development and plasticity; physiological response to the environment; and sexual dimorphism. A common feature that is emerging from these investigations concerns the dynamic nature of transcriptome evolution as indicated by rapid changes in the overall pattern of gene expression, the differential expression of numerous genes with unknown function, and the incorporation of novel, lineage-specific genes into the transcriptional profile.

[Show abstract][Hide abstract]ABSTRACT: Individual differences in behaviour are often consistent across time and contexts, but it is not clear whether such consistency is reflected at the molecular level. We explored this issue by studying scouting in honeybees in two different behavioural and ecological contexts: finding new sources of floral food resources and finding a new nest site. Brain gene expression profiles in food-source and nest-site scouts showed a significant overlap, despite large expression differences associated with the two different contexts. Class prediction and 'leave-one-out' cross-validation analyses revealed that a bee's role as a scout in either context could be predicted with 92.5% success using 89 genes at minimum. We also found that genes related to four neurotransmitter systems were part of a shared brain molecular signature in both types of scouts, and the two types of scouts were more similar for genes related to glutamate and GABA than catecholamine or acetylcholine signalling. These results indicate that consistent behavioural tendencies across different ecological contexts involve a mixture of similarities and differences in brain gene expression.

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DOI: 10.1126/science.1213962, 1225 (2012);335 Science et al.Zhengzheng S. LiangMolecular Determinants of Scouting Behavior in Honey Bees This copy is for your personal, non-commercial use only. clicking here.colleagues, clients, or customers by , you can order high-quality copies for yourIf you wish to distribute this article to others

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Updated information and services, ): June 16, 2012 www.sciencemag.org (this information is current as of http://www.sciencemag.org/content/335/6073/1225.full.htmlversion of this article at: including high-resolution figures, can be found in the onlinehttp://www.sciencemag.org/content/suppl/2012/03/07/335.6073.1225.DC1.html can be found at: Supporting Online Material http://www.sciencemag.org/content/335/6073/1225.full.html#ref-list-1, 2 of which can be accessed free:cites 16 articlesThis article http://www.sciencemag.org/cgi/collection/geneticsGeneticssubject collections:This article appears in the following registered trademark of AAAS. is aScience 2012 by the American Association for the Advancement of Science; all rights reserved. The title Copyright American Association for the Advancement of Science, 1200 New York Avenue NW, Washington, DC 20005. (print ISSN 0036-8075; online ISSN 1095-9203) is published weekly, except the last week in December, by the Science on June 16, 2012www.sciencemag.orgDownloaded from

seeking more strongly than did previous scoutassays (3, 5, 7). A large screened outdoor en-closure provided experimental control of foodsources under otherwise naturalistic conditions.Foragers from a glass-walled observation hivewere trained to a training feeder that initially wasthe only food source available to them. After 2to 3 days of training, a novel feeder with differ-ent visual and odor cues was placed at anotherlocation in the enclosure. The foraging bees thushad two possible food sources, familiar andnovel; some bees discovered the novel feederand switched to it. This procedure was repeatedon several consecutive days, and each time thenovel feeder was given new visual and odorcues and placed in a new location. Only beesthat switched to two or more different novelfeeders, after being seen at least once at thetraining feeder, were collected as scouts. Theserigorous criteria minimized the possibility of iden-tifying scouts on the basis of an accidental dis-covery of a novel feeder. The proportion of scoutbees identified with this assay (31.2, T 9.7% SD,n = 182 bees, six trials) is roughly consistentwith what has been observed under more naturalconditions (3–5), suggesting that accidental dis-coveries of novel feeders were not a major sourceof error. Bees that met our criteria for identify-ing food scouts were collected to compare theirbrain gene expression with that of control non-scouts (foragers that were never observed toswitch to a novel feeder).Whole-genome microarray analysis revealeda large neurogenomic signature for scouting be-havior in the bee brain. Sixteen percent (1219out of 7539) of the transcripts on the microarrayshowed significant (false discovery rate <0.05)differences in mRNA abundance between scoutsand non-scouts (table S3, A and B, and tableS4). Among the differentially expressed geneswere several related to catecholamine, glutamate,andg-aminobutyricacid(GABA)signaling,whichare involved in regulating novelty seeking andreward in vertebrates (1, 2, 8). For example, thedown-regulation of a dopamine receptor gene inhoney bee scouts parallels results for a similargene in individual mammals that are prone tonovelty seeking (9). These signaling systemsalso are implicated in personality differences be-tween humans that are related to novelty seeking(10, 11).Quantitativereverse-transcriptasepolymerasechain reaction analysis confirmed the microrar-ray results for five genes related to catechola-mine, glutamate, and GABA signaling (Fig. 2Aand fig. S1, A and B): D1-type dopamine recep-tor DopR1, glutamate transporters Eaat-2 andVglut, AMPA-type glutamate receptor Glu-RI,and GABA transporter Gat-a. Three addition-al catecholamine receptor genes also were dif-ferentially expressed but were undetected inmicroarray analysis:DopR2(D1-type)(12),Octb2R(b-adrenergic type octopamine receptor), andOctR1(a-adrenergictype)(13)(fig.S1BandtablesS1 and S2).Linear discriminant analysis (LDA) showeda strong separation between scouts and non-scoutsbased on the expression values for 10 neural sig-naling genes related to catecholamine, glutamate,and GABA signaling (Fig. 2B). In addition, weused these 10 genes to show that scouts identifiedwith either the new feeder–discovery assay or thehive-moving assay showed strong similarities inbrain gene expression to each other (fig. S2).The association between scouting and cate-cholamine, glutamate, and GABA signaling path-ways could reflect effects of this behavior onbrain gene expression or effects of individual dif-ferences in these pathways on scouting, or both.We used the transcriptomic results as the basis fordesigning experiments to test causal relation-ships,hypothesizingthatneurochemicaltreatmentwouldinfluencescoutingbehavior.Wetestedthishypothesiswiththehive-movingassay,becauseitresultsinrapididentificationofnumerousscouts.We collected non-scouts and provided them witha chronic (25 to 30 hours) oral neurochemicaltreatment(asspecifiedinthenextparagraph) incages (20 bees per cage) in their hive beforemoving it overnight to a location outside thecolony’s original home range.Behavioral observations the following morn-ing (14 hours after stopping the treatment) re-vealed that glutamate [monosodium glutamate(MSG)] caused a significant increase in scout-ing (Fig. 3A), whereas the vesicular glutamatetransport blocker Chicago Sky Blue signifi-cantly attenuated the MSG effects (Fig. 3B).Octopamine caused a weaker, but still signif-icant, increase in scouting (Fig. 3A). These re-sults are consistent with predictions based onmicroarray analysis. In contrast, dopamine antag-onists caused a significant decrease in scouting(Fig. 3C), which was contrary to microarray-basedprediction. Effects were not seen in all trials (figs.S3 to S5), suggesting that factors such as foodavailability, colony conditions, worker genotype,or other unknown variables also affect the prob-ability of becoming a scout. The treatments didFFig. 1. (A) Consistent novelty-seeking behavior across different contexts. Nest scouts were significantlymore likely to later act as food scouts than were non-scout swarm members. The graph shows theprobabilities of food scouting for nine trials: four natural swarms and five artificial swarms, with eightdifferent colonies (Fisher’s exact test, 2-tailed test; *P < 0.05, **P < 0.01, ***P < 0.001), and theoverall mean probabilities [least-square means and standard errors; mixed-model analysis of variance(ANOVA), 2-tailed test]. (B) Feeder-discovery assay for identifying food scouts. Additional details are inthe text and supporting online material.9 MARCH 2012VOL 335SCIENCEwww.sciencemag.org1226REPORTS on June 16, 2012www.sciencemag.orgDownloaded from

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not cause excess mortality (table S6), aberrantlocomotion, hyperactivity, or a general increasein foraging activity (fig. S6), and they were dose-dependent (fig. S7), which suggests that therewere specific treatment effects on scouting behav-ior. GABA or a GABA receptor agonist (TACA)did not affect the probability of scouting (fig.S8), so the role of this neurotransmitter in beescouting remains unclear.Multiple neurotransmitter systems appear tobe involved in the regulation of scouting in honeybees, but it is not known how they interact at thecircuit level. Glutamatergic and dopaminergic neu-rons are both found in the vertical lobes ofthe mushroom bodies, a part of the insect braininvolved in reward learning (14, 15). DopR1 andEaat-2 gene expression is colocalized to the sametype of interneurons that provide sensory inputinto these lobes (16, 17). These findings, togetherwith our own, suggest the vertical lobes of themushroom bodies as one possible neuroanatom-ical locus for novelty-seeking behavior in honeybees, although other brain regions are probablyinvolved as well.Our results demonstrate intriguing parallelsbetween honey bees and humans in novelty-seeking behavior. Although the molecular mech-anisms that produce this behavioral variation aresimilar, it is unknown whether both species in-herited them from a common ancestor or evolvedthem independently. Given the phylogenetic sep-aration of bees and humans, we believe it islikely that these mechanisms represent part of abasic tool kit that has been used repeatedly inthe evolution of behavior. Further support forthis view comes from the finding that individualdifferences in food-searching behavior in nem-atodes (Caenorhabditis elegans) are caused, inpart, by noncoding polymorphisms in tyraminereceptor 3, which encodes a receptor for a cate-cholamine closely related to octopamine and do-pamine (18).It is common to look to animal models togenerate insights that may be applicable to hu-man behavior. Our findings highlight the poten-tial of the converse—using insights from humanresearch to further elucidate the molecular basisof animal behavior. Animal studies, informed byinferences from human research, might in turnhelp identify evolutionarily conserved molecularmechanisms underlying consistent differences invarious behaviors among humans, thus helpingus better understand how and why these behav-ioral differences exist.References and Notes1. M. T. Bardo, R. L. Donohew, N. G. Harrington,Behav. Brain Res. 77, 23 (1996).2. A. D. Fidler et al., Proc. Biol. Sci. 274, 1685 (2007).3. T. zu Oettingen-Spielberg, Z. Vgl. Physiol. 31, 454(1949).4. M. Lindauer, Z. Vgl. Physiol. 34, 299 (1952).5. T. D. Seeley, Behav. Ecol. Sociobiol. 12, 253(1983).6. T. D. Seeley, Honeybee Democracy (Princeton Univ. Press,Princeton, NJ, 2010).Fig. 3. Glutamate or octopamine treatment increased the probability of scouting, whereas dopamineantagonist treatment decreased it (*P < 0.05, ***P < 0.0001). (A) Oral administration of MSG to non-scouts in sugar syrup (20 mg/ml) caused a significant effect in 7 out of 12 trials (with 11 colonies) over2 years, an overall 73% increase in scouting probability as compared to sucrose-fed–only control bees(P < 0.0001, mixed-model ANOVA, 2-tailed test). Octopamine (OA) treatment (4 mg/ml) caused asignificant effect in 3 out of 10 trials (in nine colonies) over 2 years, an overall 37% increase inscouting probability (P < 0.05). Statistical tests were performed on square root–transformed data; thegraph represents the untransformed mean T SE of 12 trials for MSG (with 11 colonies) and 10 trials foroctopamine (with 9 colonies); results of individual trials are shown in figs. S3 and S4. (B) The glutamatevesicular transporter blocker Chicago Sky Blue (CSB) (4 mg/ml) blocked the effect of MSG on scouting(P < 0.05, least-square mean T SE for four previously MSG-responsive colonies; results of individualtrials are shown in fig. S3). (C) Non-scout foragers treated with dopamine antagonists (DAA) (either theD1-receptor antagonist SCH-23390, the “pan-receptor” antagonist Flupenthixol, or both) showed anoverall 44% decrease in scouting probability in seven trials over three colonies (P < 0.05, the graphrepresents least-square mean T estimated error; mixed-model ANOVA, 2-tailed test; results of individualtrials are shown in fig. S5). The probability of scouting was calculated from the proportion of foragers ineach treatment group that exhibited scouting behavior, based on a precise count of foragers whenreleasing them from treatment cages.RI-Fig. 2. Transcriptomic analyses of individual differences in novelty-seeking between food scouts (S) andnon-scouts (NS) (n = 20 bees per group). (A) Selected microarray results highlight differences in brainexpression for 10 dopamine, octopamine, glutamate, or GABA signaling genes related to noveltyseeking, motivation, and reward in vertebrates. DopR2 and OctR1 did not show significant differencesin expression (in the latter case, probably because of very low expression levels). GABA transporter 1Agene (Gat-a) expression was one of the best correlates of scouting behavior (permutation t test, P <0.05). (B) Results of LDA for genes shown in (A) demonstrate clear separation between most scouts andnon-scouts based on differences in brain gene expression (standardized expression values: mean = 0,SD = 1). This plot of LD1 versus LD2 accounted for 82% of the variation in brain gene expressionacross scouts and non-scouts (n = 20 bees per group). S1, S2, S3 and N1, N2, N3: scouts and non-scouts, respectively, from three different colonies.www.sciencemag.orgSCIENCEVOL 335 9 MARCH 20121227REPORTS on June 16, 2012www.sciencemag.orgDownloaded from

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7. C. Dreller, Behav. Ecol. Sociobiol. 43, 191 (1998).8. J. B. Becker, R. L. Meisel, Handbook of Neurochemistryand Molecular Neurobiology: Behavioral Neurochemistry,Neuroendocrinology and Molecular Neurobiology(Springer, New York, 2007).9. D. Viggiano, D. Vallone, H. Welzl, A. G. Sadile,Behav. Genet. 32, 315 (2002).10. R. P. Ebstein et al., Nat. Genet. 12, 78 (1996).11. J. Benjamin et al., Nat. Genet. 12, 81 (1996).12. J. A. Mustard et al., Brain Res. Mol. Brain Res. 113, 67(2003).13. P. D. Evans, B. Maqueira, Invert. Neurosci. 5, 111(2005).14. F. W. Schürmann, K. Elekes, M. Geffard, Cell Tissue Res.256, 399 (1989).15. G. Bicker, S. Schäfer, O. P. Ottersen, J. Storm-Mathisen,J. Neurosci. 8, 2108 (1988).16. R. Kucharski, E. E. Ball, D. C. Hayward, R. Maleszka, Gene242, 399 (2000).17. P. T. Kurshan, I. S. Hamilton, J. A. Mustard, A. R. Mercer,J. Comp. Neurol. 466, 91 (2003).18. A. Bendesky, M. Tsunozaki, M. V. Rockman, L. Kruglyak,C. I. Bargmann, Nature 472, 313 (2011).Acknowledgments: Special thanks to M. K. Carr-Markell andJ. Recchia-Rife for extensive help in the field. We also thankthe following: C. Nye and K. Pruiett (bee management);A. Brockmann, P. Date, J. Dotterer, L. Felley, M. Girard,S. Kantarovich, H. S. Pollock, and M. Wray (field assistance);T. Newman (molecular studies); S. Aref and A. Toth (statistics);E. Hadley (graphics); and A. M. Bell, D. F. Clayton, R. C. Fuller,J. S. Rhodes, C. W. Whitfield, and members of the Robinsonlaboratory (review of the manuscript). Supported by NSFFrontiers in Biological Research grant EF 0425852 (B. L. Schatz,PI, BeeSpace Project); NIH Director’s Pioneer Award1DP1OD006416 (G.E.R); and the Illinois SociogenomicsInitiative (G.E.R). Microarray data meet Minimum InformationAbout Microarray Experiment (MIAME) standards and areavailable at ArrayExpress (www.ebi.ac.uk/arrayexpress,#E-MTAB-491). Z.S.L. and G.E.R. conceived the project, designedthe experiments and wrote the paper; Z.S.L. performedsample collection, molecular and field experiments, andanalyses; T.N. and S.L.R.-Z. performed microarray experimentsand statistical analyses, respectively; and H.R.M. and T.D.S.contributed to protocol development and sample collectionand co-wrote the paper.Supporting Online Materialwww.sciencemag.org/cgi/content/full/335/6073/1225/DC1Materials and MethodsSOM TextFigs. S1 to S8Tables S1 to S6References14 September 2011; accepted 1 February 201210.1126/science.1213962Atomic View of a Toxic AmyloidSmall OligomerArthur Laganowsky,1* Cong Liu,1Michael R. Sawaya,1Julian P. Whitelegge,2Jiyong Park,1Minglei Zhao,1Anna Pensalfini,3Angela B. Soriaga,1Meytal Landau,1Poh K. Teng,1Duilio Cascio,1Charles Glabe,3David Eisenberg1†Amyloid diseases, including Alzheimer’s, Parkinson’s, and the prion conditions, are each associatedwith a particular protein in fibrillar form. These amyloid fibrils were long suspected to be thedisease agents, but evidence suggests that smaller, often transient and polymorphic oligomersare the toxic entities. Here, we identify a segment of the amyloid-forming protein aB crystallin,which forms an oligomeric complex exhibiting properties of other amyloid oligomers: b-sheet–richstructure, cytotoxicity, and recognition by an oligomer-specific antibody. The x-ray–derivedatomic structure of the oligomer reveals a cylindrical barrel, formed from six antiparallel proteinstrands, that we term a cylindrin. The cylindrin structure is compatible with a sequence segmentfrom the b-amyloid protein of Alzheimer’s disease. Cylindrins offer models for the hitherto elusivestructures of amyloid oligomers.Sprotein fibrils that have long been taken as thedefining feature of these disorders but insteadare lower molecular weight entities, often termedsmall amyloid oligomers (1–7). These oligomersare not generally stable aggregates; they appearas transient speciesduringtheconversionof theirmonomeric precursors to more massive, stablefibrils, and sometimes they appear as an ensem-ble of sizes and shapes. This polymorphic andtime-dependent nature of small amyloid oligo-mers has made it difficult to pin down their as-tudies from many laboratories have sug-gestedthatthemolecularagentsinamyloid-related conditions are not the associatedsembly pathways, their stoichiometries, theiratomic-level structures, their relationship to fi-brils, and their pathological actions (1, 8–10).What has emerged is a consensus, minimal def-inition of small amyloid oligomers: They arenoncovalentassembliesofseveralidenticalchainsof proteins also known to form amyloid fibrils;the oligomers exhibit greater cytotoxicity than ei-therthemonomerorfibrilsformedfromthesameprotein; in many cases, the oligomer is recog-nized by a “conformational” antibody (A11) thatbinds oligomers but not fibrils, regardless of thesequence of the constituent protein (5). This sug-gests that oligomers display common conforma-tion features that differ from those of fibrils (11).In seeking to better define small amyloidoligomers, we chose to work with aB crystallin(ABC). This protein is a chaperone (12–14) thatforms amyloid fibrils (15), but the fibrils formmore slowly than those of the b-amyloid peptide(Ab) or islet amyloid polypeptide (IAPP), so thatthe oligomeric state may be trapped before theonsetoffibrillization.Wehaveidentifiedasegmentof ABC that forms a relatively stable small oligo-mer, which satisfies the definition of a small amy-loid oligomer given in the preceding paragraph.We identified the oligomer-forming segmentof ABC by inspection of its three-dimensional(3D) structure (16) and by applying the Rosetta-Profile algorithm to its sequence. This algorithmidentifies sequence segments that form the steric-zipperspinesofamyloidfibrils(17,18).Wenotedthat two segments of high amyloidogenic pro-pensity,withsequencesKVKVLGandGDVIEV(where D indicates Asp; E, Glu; G, Gly; I, Ile;K, Lys; and V, Val), share the same Gly residue95 at the C terminus of the first segment and theN terminus of the second; moreover, the entire11-residue segment KVKVLGDVIEV forms ahairpinloopinthe3DstructureofABC(Fig.1A),with Gly at its center. As predicted, the sec-ond six-residue segment GDVIEV, termed G6V(Table 1 defines the structures described in thisreport), forms fibrils and microcrystals (fig. S1).The microcrystals enabled us to determine theatomic structure of G6V (fig. S2), which provedto be a standard class 2 steric zipper (19), es-sentially an amyloid-like protofilament.ThehairpinsegmentKVKVLGDVIEV(termedK11V) formed both amyloid fibrils and oligo-mers. Upon shaking at elevated temperature,K11V forms fibrils similar to those of the parentprotein(ABC)fromwhichthesegmentisderived(15) and similar to those of a tandem repeat ofK11VV2L(K11V-TR,seebelow)(Fig.1B;fig.S1,B and C; and table S1). The fibrils range from 20to 100 nm in diameter as viewed by electron mi-croscopy(fig.S1).X-raydiffractionofdriedfibrilsdisplayed rings at 4.8 and 12 Å resolutions, con-sistent with the signature cross-b pattern of amy-loid fibrils (fig. S1C). The amyloid fibrils ofK11V-TRbindthespecificamyloiddyecongored,producing apple-green bifringerance under polar-izedlight(fig.S1D),andareimmunoreactivewiththe fibril-specific, conformation-dependent anti-body OC (Fig. 1E) (20). Together these resultsprove that the segments G6V, K11V, and K11V-TR are all capable of converting to the amyloidstate (21, 22), as is their parent protein, ABC.Underphysiologicalconditions,the segmentsK11V, K11V-TR, and a sequence variant withLeu replacing Val at position 2 (K11VV2L) allform stable small oligomers intermediate in size1Department of Biological Chemistry and Department ofChemistry and Biochemistry, University of California LosAngeles (UCLA), Howard Hughes Medical Institute (HHMI),UCLA-DOE Institute for Genomics and Proteomics, Los Angeles,CA 90095, USA.2The Neuropsychiatric Institute (NPI)–SemelInstitute for Neuroscience and Human Behavior, UCLA, LosAngeles, CA 90024, USA.3Department of Molecular Biol-ogy and Biochemistry, University of California, Irvine, CA92697, USA.*Present address: Department of Chemistry, Chemistry Re-search Laboratory, University of Oxford, Oxford, UK.†To whom correspondence should be addressed. E-mail:david@mbi.ucla.edu9 MARCH 2012 VOL 335SCIENCEwww.sciencemag.org1228REPORTS on June 16, 2012www.sciencemag.orgDownloaded from